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使用多个稀疏先验对癫痫尖峰进行源定位。

Source localization of epileptic spikes using Multiple Sparse Priors.

机构信息

LEICI Instituto de Investigaciones en Electrónica, Control y Procesamiento de Señales, Universidad Nacional de La Plata - CONICET, Argentina.

Department of Neurosurgery, Huashan Hospital of Fudan University, Shanghai, China.

出版信息

Clin Neurophysiol. 2021 Feb;132(2):586-597. doi: 10.1016/j.clinph.2020.10.030. Epub 2020 Dec 3.

DOI:10.1016/j.clinph.2020.10.030
PMID:33477100
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7971150/
Abstract

OBJECTIVE

To evaluate epileptic source estimation using multiple sparse priors (MSP) inverse method and high-resolution, individual electrical head models.

METHODS

Accurate source localization is dependent on accurate electrical head models and appropriate inverse solvers. Using high-resolution, individual electrical head models in fifteen epilepsy patients, with surgical resection and clinical outcome as criteria for accuracy, performance of MSP method was compared against standardized low-resolution brain electromagnetic tomography (sLORETA) and coherent maximum entropy on the mean (cMEM) methods.

RESULTS

The MSP method performed similarly to the sLORETA method and slightly better than the cMEM method in terms of success rate. The MSP and cMEM methods were more focal than sLORETA with the advantage of not requiring an arbitrary selection of a hyperparameter or thresholding of reconstructed current density values to determine focus. MSP and cMEM methods were better than sLORETA in terms of spatial dispersion.

CONCLUSIONS

Results suggest that the three methods are complementary and could be used together. In practice, the MSP method will be easier to use and interpret compared to sLORETA, and slightly more accurate and faster than the cMEM method.

SIGNIFICANCE

Source localization of interictal spikes from dense-array electroencephalography data has been shown to be a reliable marker of epileptic foci and useful for pre-surgical planning. The advantages of MSP make it a useful complement to other inverse solvers in clinical practice.

摘要

目的

评估使用多个稀疏先验（MSP）反演方法和高分辨率个体头部电模型进行癫痫源估计。

方法

准确的源定位依赖于准确的头部电模型和适当的反演求解器。在 15 名癫痫患者中使用高分辨率个体头部电模型，以手术切除和临床结果作为准确性的标准，将 MSP 方法的性能与标准化低分辨率脑电磁层析成像（sLORETA）和均值相干最大熵（cMEM）方法进行比较。

结果

MSP 方法在成功率方面与 sLORETA 方法表现相似，略优于 cMEM 方法。MSP 和 cMEM 方法比 sLORETA 方法更具焦点性，其优点是不需要任意选择超参数或对重建电流密度值进行阈值处理来确定焦点。MSP 和 cMEM 方法在空间分散性方面优于 sLORETA。

结论

结果表明，这三种方法是互补的，可以一起使用。在实践中，与 sLORETA 相比，MSP 方法将更易于使用和解释，并且比 cMEM 方法略为准确和快速。

意义

从密集脑电图数据中定位发作间期棘波已被证明是癫痫灶的可靠标志物，对术前计划有用。MSP 的优点使其成为临床实践中其他反演求解器的有用补充。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac24/7971150/d1e81ebfe48c/nihms-1666397-f0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac24/7971150/870cdd23d362/nihms-1666397-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac24/7971150/a2ce19c82076/nihms-1666397-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac24/7971150/fe9b2e41f703/nihms-1666397-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac24/7971150/e38a7b101be6/nihms-1666397-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac24/7971150/de9842150c15/nihms-1666397-f0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac24/7971150/42cbc102fe91/nihms-1666397-f0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac24/7971150/d1e81ebfe48c/nihms-1666397-f0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac24/7971150/870cdd23d362/nihms-1666397-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac24/7971150/a2ce19c82076/nihms-1666397-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac24/7971150/fe9b2e41f703/nihms-1666397-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac24/7971150/e38a7b101be6/nihms-1666397-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac24/7971150/de9842150c15/nihms-1666397-f0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac24/7971150/42cbc102fe91/nihms-1666397-f0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac24/7971150/d1e81ebfe48c/nihms-1666397-f0007.jpg

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